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Clustering Categorical Data Using Community Detection Techniques
With the advent of the k-modes algorithm, the toolbox for clustering categorical data has an efficient tool that scales linearly in the number of data items. However, random initialization of cluster centers in k-modes makes it hard to reach a good clustering without resorting to many trials. Recent...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Hindawi
2017
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753022/ https://www.ncbi.nlm.nih.gov/pubmed/29430249 http://dx.doi.org/10.1155/2017/8986360 |